Atmosphere (Jul 2022)
Impacts of Transition Approach of Water Vapor-Related Microphysical Processes on Quantitative Precipitation Forecasting
Abstract
The water vapor-related microphysical processes (WVRMPs) in cloud microphysics schemes are crucial to the formation and dissipation of clouds, which have a significant impact on the quantitative precipitation forecasting of numerical weather prediction models. In this study, a well physics-based parallel-split transition approach (PSTA) to compute the WVRMPs from the same temperature and humidity state is developed and compared with the original sequential-update transition approach (SUTA) in a double-moment cloud microphysics scheme. Case study and batch experiments were carried out to investigate their different impacts on the clouds and precipitation simulated by the Global/Regional Assimilation and Prediction System (GRAPES) regional 3 km high-resolution model of the China Meteorological Administration (CMA), named CMA-MESO. The results show that the PSTA experiment tends to simulate a narrower and more concentrated precipitation area with a higher-intensity center compared to those of the SUTA experiment, which is more consistent with the observations. In the cold region, the net transition rates of WVRMPs from the PSTA experiment with more ice-phase hydrometeors are higher than those from the SUTA experiment. While in the warm region, the condensation and evaporation rates with violent fluctuation simulated by the SUTA are significantly larger than those from the PSTA experiment, resulting in less precipitation. The batch experiments indicate that the equitable threat scores (ETSs) of 24-h precipitation simulated by the PSTA are just slightly better than those of the SUTA, yet its ETSs of 48-h precipitation have been systematically improved for all magnitude levels against the SUTA. It is demonstrated that more attention should be paid to the reasonable treatments of the WVRMPs in developing cloud microphysics schemes.
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